The present invention relates to wireless communication systems. More particularly, the present invention relates to spatial mapping matrix searching in wireless communication systems.
Modern wireless communication systems generally must be capable of providing voice and broadband data services. Many wireless communication systems, such as one that deploys the third generation partnership project (3GPP) standard for LTE or IEEE 802.16 series (e.g. WiMax standard), incorporate applying transmit beamforming to antenna diversity over multiple-input multiple-output channels (MIMO channels) to increase the data transfer rate of the data services. The data transfer rate may be improved by increasing the diversity gain and/or coding gain of the wireless communication systems adapting the antenna diversity. This may be accomplished by providing a feedback of information such as a spatial mapping matrix, including information processed by a receiver, such as a mobile station (MS), from its received signals transmitted by a transmitter, such as a base station (BS), to the transmitter to adjust or tune phases or power consumption of the antennae. Methods for searching a spatial mapping matrix therefore play an important role in improving data service.
The beamforming methods for finding a closed-loop spatial mapping matrix for MIMO system may include an eigen-beamforming method, a Grassmannian spatial mapping method, and an equal-gain spatial mapping method. The eigen-beamforming method selects eigenvectors that corresponds to maximum eigenvalues of a channel matrix representing the channel response of the MIMO channel to archive largest channel capacity. However, the large amount of feedback information, to which the desired eigenvectors and eigen decomposition results of the channel matrix information are embedded, renders this method hard to be visualized in real world system. The Grassmannian spatial mapping matrix method is a codebook construction method and it works well in some environment having MIMO channels. However, the optimal codebook may be difficult to construct. The equal gain spatial mapping matrix method only changes the phase of each combined signal streams and has no PAPR between different transmitted antennae. The exhaustive searching for any phase combination in the spatial mapping matrices method may be applicable of finding the best achievable solution, i.e. the spatial mapping matrix. However, this method may lack a closed form solution for its spatial mapping matrix in most MIMO channels.
It may therefore be desirable to have an equal gain spatial mapping matrix searching method having closed form solution for finding spatial mapping matrices for wireless communication systems comprising MIMO channels.